Chronic heart failure (HF) occurs when a heart is unable to consistently pump blood at an adequate rate in response to the filling pressure. To improve the ability of the heart to pump blood, congestive heart failure patients, classified as having New York Heart Association (NYHA) class status of II to IV HF, may require therapy, such as may be provided by implantable medical devices (IMDs) such as implantable cardioverter defibrillators (ICDs) and cardiac resynchronization devices with defibrillation capability (CRT-Ds). Despite using IMDs to improve heart function, some HF patients may require hospitalization. Global health care systems incur billions of dollars each year due to heart failure hospitalizations (HFHs). Identifying patients at risk of HFH to enable timely intervention and prevent expensive hospitalization remains a challenge.
IMDs may be configured to acquire data for a variety of diagnostic metrics that change with HF status and collectively have the potential to signal an increasing risk of HFH. Diagnostic parameter data collected by IMDs include activity, day and night heart rate (NHR), atrial tachycardia/atrial fibrillation (AT/AF) burden, mean rate during AT/AF, percent CRT pacing, number of shocks, and intrathoracic impedance. Additionally, preset or programmable thresholds for diagnostic metrics, when crossed, trigger a notification, referred to as device observation. Each device observation is recorded in an IMD report.
One conventional method for determining heart failure risk status is described in U.S. Publication No. 2012/0253207 A1, entitled “Heart Failure Monitoring,” by Sarkar et al., which is incorporated herein by reference in its entirety. In this example, the “High” risk level is associated with 15% or greater risk that the patient will be hospitalized. The “Low” category was chosen to represent diagnostic evaluations where the metric state for all the patient metrics was mostly “Low” (e.g., a risk score of less than ˜5%). The “Medium” category comprises of all other metric state combinations that did not get classified as either “High” or “Low.” In some cases, a clinician may need to evaluate and respond to numerous high and medium risk level alerts.